The two main tasks performed on time-series data are forecasting and classification. Forecasting seeks to predict real-valued numbers from given time-series data, referred to as regression. Many forecasting Transformers for time-series data have been developed in the recent literature [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]}, [11]}. The classification task involves categorizing the given time-series data into one or more target classes. There have been many recent advancements for time-series Transformers for classification tasks [12]}, [13]}, [14]}, [15]}, [16]}. All of the time-series Transformer-based models discussed in this tutorial focus on one of these two tasks. Some of these models can accomplish both tasks after small modifications in the last layer and the loss function.
